In this paper, we present and compare two commonly used contrastive learning approaches for enhancing ABSA performance.
May 2, 2024 · Several methods try to solve the aspect extraction task needed in sentiment analysis by using Deep Learning techniques in specific domains.
In this paper, we revisit ABSA from a novel perspective by deploying a novel supervised contrastive learning framework to leverage the correlation and ...
Oct 18, 2024 · The model employs the Contrastive Loss function to enhance learning. Our experiments, conducted on datasets from restaurants, laptops, and ...
Missing: Improving | Show results with:Improving
This repository contains the PyTorch code and implementation for the paper Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning.
In this work, we introduce GEN-SCL-NAT, which consists of two techniques for improved structured generation for ACOS quadruple extraction.
Nov 14, 2022 · In this work, we introduce GEN-SCL-NAT, which consists of two techniques for improved structured generation for ACOS quadruple extraction.
By employing supervised contrastive learning, models for ABSA can be trained using both labeled and unlabeled data to boost performance. In this research, we ...
Missing: Improving | Show results with:Improving
Oct 15, 2024 · Through contrastive learning, we constructed positive and negative sample pairs, enabling the model to more accurately identify and distinguish ...
In this work, we introduce GEN-SCL-NAT, which consists of two techniques for improved struc- tured generation for ACOS quadruple extrac- tion. First, we propose ...